\section{Related Work}
Recent years data centers have seen great changes. Multi-tenant public cloud such as Amazon EC2 and ever larger data centers have been popular. A huge amount of data-intensive and web serving applications have become dominant workloads in the data center. The storage and network also evolve to better serve these applications. New data center network architectures also emerge, e.g., c-through~\cite{c-through} proposes a hybrid packet and circuit switched network architecture to supply high bandwidth to applications. Helios~\cite{Helios} is a hybrid electrical/optical switch architecture to ease the deployment of modular data centers. Flyways~\cite{flyaways} proposes to use the wireless links to selectively add capacity where needed. At the same time, many cloud systems adopt key-value stores or NoSQL systems such as BigTable, HBase, Cassandra and Voldemort, and different components in these distributed storage systems rely on the network to communicate with each other.

Some research works already reveal that the network architecture and how network behaves have great impact on storage performance. Flat Data center Storage (FDS)~\cite{flat-datacenter-storage} is a recent work which exploits full bisection bandwidth networks to obviate the need of data locality and enables to expose all of a cluster's disk bandwidth to applications. Incast~\cite{incast} problem could happen when a client synchronously reads fragments of a data block from multiple data sources.

Yet little work is done about the interaction between storage and network. For example, Pisces~\cite{pisces} provides performance isolation and fairness between tenants, but it assumes network is well provisioned. On the other hand, FairCloud~\cite{faircloud} proposes network allocation policies to better achieve fairness in cloud environment but does not touch storage. Moreover, network optimizations for data-intensive applications such as Orchestra~\cite{orchestra} often assume all data can be accommodated in memory and therefore ignore the storage I/O cost. But ~\cite{c-through} points out that these applications can still be bottlenecked by intensive disk I/O operations.

Conventional network measurement such as~\cite{wild} usually concerns about the network traffic as a whole rather than pays particular attention to storage system traffics.
